Strong demand is pushing the emergence of solutions and tools that leverage artificial intelligence ( AI ) to navigate the complexities of sustainability compliance and risks, in general, and fund naming, in particular.

The launch on February 5 of an AI-driven sustainability fund naming solution by London-based Clarity AI, for example, is in response to the increasing regulatory demands and greenwashing scrutiny that have resulted from the proliferation of new sustainability fund labels in recent years.

Some of these demands, like the UK Financial Conduct Authority’s sustainability disclosure requirements, are driven by regulators, while others, such as France’s SRI label and Germany’s FNG, are government or industry-led.

Complying with all these regulatory requirements while using traditional analytical tools, experts say, has become increasingly challenging; and, as a result, AI-driven analytical tools are increasingly in demand.

“Sustainability regulations and labels are proliferating, making it increasingly challenging for fund managers to keep up,” notes Tom Willman, Clarity AI’s regulatory lead. “A significant amount of resources is tied up in regulatory obligations. These could be better used to develop sustainable solutions that support end-investors’ sustainability goals, and technology is key to making this process more efficient.”

AI-driven sustainability solutions and tools are also currently being offered by rating agency Sustainalytics and MSCI ESG Research, both of whom use AI tools to assess fund sustainability risks and compliance.

Sustainability solution provider Arabesque AI also employs machine learning for environmental, social and governance ( ESG ) analysis and sustainable investment strategies.

In terms of sustainable fund naming and compliance, AI is being used for automated compliance monitoring by analyzing fund portfolios against sustainability regulations, such as the EU’s Sustainable Finance Disclosure Regulation and the US Securities Exchange Commission’s ESG fund rules.

AI-driven solutions are also being used to process vast amounts of ESG data from multiple sources, including financial reports, third-party ESG ratings and company disclosures.

And AI solutions are also being used as a natural language processing tool for fund naming, such as for evaluating fund descriptions and marketing materials to detect potential greenwashing ( misleading sustainability claims ), as well as for real-time sustainability score calculation, and portfolio alignment and rebalancing.

In the case of Clarity AI, the company claims its solution addresses the challenges of monitoring funds across complex metrics and frameworks – that are unique to each market – by providing a user-friendly platform that brings all the information into a single screen.

Henry Waind, the company’s product lead, states: “The goal is to reduce the amount of time fund managers spend on identifying potential investments that fall short of the standards and on understanding the cause for non-compliance, in order to decide on the best course of action.”